This invention relates generally to medical diagnostic systems. In particular, the present invention relates to method and apparatus for automatically identifying delay of cardiac tissue motion and deformation.
Patients suffering from conduction diseases may develop mechanical asynchrony, meaning that the various parts of the heart contract at different times. When the right and left ventricles do not beat with proper timing, the heart is not functioning optimally. The use of Tissue Velocity Imaging (TVI) and strain imaging to quantify the amount of synchrony between the right and left ventricle (interventricular) and within the left ventricle (intraventricular) has been suggested. One of the typical measurements is the time delay from onset of QRS to the peak in systolic velocity. Variation in this parameter between the different parts of the heart may indicate asynchrony. Other suggested parameters are the time to onset of contraction and time to onset of E-wave in velocity or strain rate.
Biventricular pacing, also known as Cardiac Resynchronization Therapy (CRT) or Ventricular Resynchronization Therapy (VRT), may help patients with asynchrony. CRT involves introducing a pacemaker with at least three leads: one in the right atrium, one in the right ventricle and one in a coronary vein of the left ventricle. The pacemaker provides an electrical signal causing the left and right ventricles to contract in synchrony, which increases the ejection fraction (EF). However, not all patients with asynchrony will benefit from this type of pacemaker.
Advanced ultrasound systems currently allow visualization of the motion and deformation of various parts of the ventricle. Unfortunately, it is not possible to automatically identify which wall, or segment of wall, is contracting earlier, and which segment(s) have delayed motion. Therefore, it is a tedious and time consuming task to manually inspect the motion or deformation pattern of each segment to assess the asynchrony.
Thus, a system and method are desired to process diagnostic data sets to easily identify the segments with delayed motion automatically, that addresses the problems noted above and others previously experienced.